Video: Can machine learning bail enterprises out of their data management woes?

The UK operation of Save the Children[1] (SCUK) works to save lives by preparing for and responding to humanitarian emergencies caused by natural disasters, disease outbreaks, and armed conflicts.

Read also: EU General Data Protection Regulation (GDPR) compliance checklist[2]

Like many charities, SCUK faces a number of challenges in fulfilling its mission. These include regulatory and compliance requirements such as the upcoming General Data Protection Regulation (GDPR),[3] which requires charities to be open about how they manage data and spend funds to avoid any suspicion of fraud; overcome "donor fatigue," where donors are contacted by numerous charities; and transparency, which requires charities to be open about how they manage their data[4].

A key data management challenge SCUK faced was trying to speed up the cleansing and loading of data into its customer relationship management[5] (CRM) system from 50-plus streams, combining donations from direct debit, online, SMS messaging, TV campaigns, and other sources.

SCUK has been using its current CRM application for about 15 years, and the system contains more than 800 tables with more than 800 million records. These include communication histories, financial transactions, and the details of more than four million contact and organization records captured since 2002.

The team handling data import was under pressure to deal with the growing volumes of complex data, and it needed to find a more efficient way to manage the data streams that would improve the quality of incoming data and better identify potential duplicate records.

The organization deployed data integration and data

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